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公开(公告)号：US11468110B2
公开(公告)日：2022-10-11
申请号：US16800415
申请日：2020-02-25
Applicant: Adobe Inc.
Inventor： Walter Wei Tuh Chang , Khoi Pham , Scott Cohen , Zhe Lin , Zhihong Ding
IPC: G06F16/532 , G06F16/583 , G06F16/538 , G06F16/33 , G06T11/60 , G06K9/62 , G06F40/279 , G06F40/247 , G06N20/00 , G06F16/242 , G06F16/28 , G06F40/30
Abstract: The present disclosure relates to an object selection system that automatically detects and selects objects in a digital image based on natural language-based inputs. For instance, the object selection system can utilize natural language processing tools to detect objects and their corresponding relationships within natural language object selection queries. For example, the object selection system can determine alternative object terms for unrecognized objects in a natural language object selection query. As another example, the object selection system can determine multiple types of relationships between objects in a natural language object selection query and utilize different object relationship models to select the requested query object.
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公开(公告)号：US20240171848A1
公开(公告)日：2024-05-23
申请号：US18058554
申请日：2022-11-23
Applicant: Adobe Inc.
Inventor： Luis Figueroa , Zhihong Ding , Scott Cohen , Zhe Lin , Qing Liu
CPC classification number: H04N23/632 , G06V10/273 , G06V10/764 , G06V10/82 , G06V10/945 , H04N5/2628
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems provide, for display within a graphical user interface of a client device, a digital image displaying a plurality of objects, the plurality of objects comprising a plurality of different types of objects. The disclosed systems generate, utilizing a segmentation neural network and without user input, an object mask for objects of the plurality of objects. The disclosed systems determine, utilizing a distractor detection neural network, a classification for the objects of the plurality of objects. The disclosed systems remove at least one object from the digital image, based on classifying the at least one object as a distracting object, by deleting the object mask for the at least one object.
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23.发明公开公开(公告)号：US20240169502A1
公开(公告)日：2024-05-23
申请号：US18058630
申请日：2022-11-23
Applicant: Adobe Inc.
Inventor： Scott Cohen , Zhe Lin , Zhihong Ding , Luis Figueroa , Kushal Kafle
IPC: G06T5/00 , G06F3/04842 , G06F3/04845 , G06T3/20 , G06V10/70 , G06V10/86
CPC classification number: G06T5/005 , G06F3/04842 , G06F3/04845 , G06T3/20 , G06V10/768 , G06V10/86 , G06T2200/24 , G06T2207/20084 , G06T2207/20104
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems detect, via a graphical user interface of a client device, a user selection of an object portrayed within a digital image. The disclosed systems determine, in response to detecting the user selection of the object, a relationship between the object and an additional object portrayed within the digital image. The disclosed systems receive one or more user interactions for modifying the object. The disclosed systems modify the digital image in response to the one or more user interactions by modifying the object and the additional object based on the relationship between the object and the additional object.
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公开(公告)号：US20240135613A1
公开(公告)日：2024-04-25
申请号：US18320664
申请日：2023-05-19
Applicant: Adobe Inc.
Inventor： Zhihong Ding , Scott Cohen , Matthew Joss , Jianming Zhang , Darshan Prasad , Celso Gomes , Jonathan Brandt
CPC classification number: G06T11/60 , G06F3/04842 , G06T3/40 , G06T5/005 , G06T7/50 , G06V10/761 , G06T2207/20084
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement perspective-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a vanishing point associated with a digital image portraying an object. Additionally, the disclosed systems detect one or more user interactions for moving the object within the digital image. Based on moving the object with respect to the vanishing point, the disclosed systems perform a perspective-based resizing of the object within the digital image.
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公开(公告)号：US20220383037A1
公开(公告)日：2022-12-01
申请号：US17332734
申请日：2021-05-27
Applicant: Adobe Inc.
Inventor： Khoi Pham , Kushal Kafle , Zhe Lin , Zhihong Ding , Scott Cohen , Quan Tran
Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that extract multiple attributes from an object portrayed in a digital image utilizing a multi-attribute contrastive classification neural network. For example, the disclosed systems utilize a multi-attribute contrastive classification neural network that includes an embedding neural network, a localizer neural network, a multi-attention neural network, and a classifier neural network. In some cases, the disclosed systems train the multi-attribute contrastive classification neural network utilizing a multi-attribute, supervised-contrastive loss. In some embodiments, the disclosed systems generate negative attribute training labels for labeled digital images utilizing positive attribute labels that correspond to the labeled digital images.
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Patent Agency Ranking
26.发明申请公开(公告)号：US20220237799A1
公开(公告)日：2022-07-28
申请号：US17158527
申请日：2021-01-26
Applicant: Adobe Inc.
Inventor： Brian Price , David Hart , Zhihong Ding , Scott Cohen
Abstract: The present disclosure relates to a multi-model object segmentation system that provides a multi-model object segmentation framework for automatically segmenting objects in digital images. In one or more implementations, the multi-model object segmentation system utilizes different types of object segmentation models to determine a comprehensive set of object masks for a digital image. In various implementations, the multi-model object segmentation system further improves and refines object masks in the set of object masks utilizing specialized object segmentation models, which results in more improved accuracy and precision with respect to object selection within the digital image. Further, in some implementations, the multi-model object segmentation system generates object masks for portions of a digital image otherwise not captured by various object segmentation models.
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公开(公告)号：US11302033B2
公开(公告)日：2022-04-12
申请号：US16518795
申请日：2019-07-22
Applicant: Adobe Inc.
Inventor： Zhihong Ding , Scott Cohen , Zhe Lin , Mingyang Ling
Abstract: The present disclosure relates to a color classification system that accurately classifies objects in digital images based on color. In particular, in one or more embodiments, the color classification system utilizes a multidimensional color space and one or more color mappings to match objects to colors. Indeed, the color classification system can accurately and efficiently detect the color of an object utilizing one or more color similarity regions generated in the multidimensional color space.
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公开(公告)号：US20210027497A1
公开(公告)日：2021-01-28
申请号：US16518795
申请日：2019-07-22
Applicant: Adobe Inc.
Inventor： Zhihong Ding , Scott Cohen , Zhe Lin , Mingyang Ling
Abstract: The present disclosure relates to a color classification system that accurately classifies objects in digital images based on color. In particular, in one or more embodiments, the color classification system utilizes a multidimensional color space and one or more color mappings to match objects to colors. Indeed, the color classification system can accurately and efficiently detect the color of an object utilizing one or more color similarity regions generated in the multidimensional color space.
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公开(公告)号：US10769738B2
公开(公告)日：2020-09-08
申请号：US15925259
申请日：2018-03-19
Applicant: Adobe Inc.
Inventor： Walter W. Chang , Zhihong Ding , Lubomira A. Dontcheva , Gregg D. Wilensky , Darshan D. Prasad , Claudia Veronica Roberts
Abstract: A tutorial for a given application may be leveraged to generate executable code that can then be executed within a native instruction service of the application. In this way, a software application may thus provide an integrated, interactive learning experience for a user, in a manner that extends beyond the instructional content included in the native instruction service, i.e., that includes at least a portion of the instructional content of the tutorial.
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公开(公告)号：US20190287197A1
公开(公告)日：2019-09-19
申请号：US15925259
申请日：2018-03-19
Applicant: Adobe Inc.
Inventor： Walter W. Chang , Zhihong Ding , Lubomira A. Dontcheva , Gregg D. Wilensky , Darshan D. Prasad , Claudia Veronica Roberts
Abstract: A tutorial for a given application may be leveraged to generate executable code that can then be executed within a native instruction service of the application. In this way, a software application may thus provide an integrated, interactive learning experience for a user, in a manner that extends beyond the instructional content included in the native instruction service, i.e., that includes at least a portion of the instructional content of the tutorial.
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